Robust stability for stochastic interval Hopfield neural networks with time delays

Author

Han, Jin-fang ; Qiu, Ji-qing ; Jia, Hui-ran ; Meng, Xiang-ting

Author_Institution

Inst. of Eng. Math., Hebei Univ. of Sci. & Technol., Shijiazhuang, China

Volume

2

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

801

Lastpage

805

Abstract

In this paper, the robust stability for a kind of stochastic interval delayed Hopfield cellular neural networks is investigated by means of the Itô formula, Razumikhin theorems, Lyapunov function and norm inequalities. several simple sufficient conditions are obtained which guarantee the robust stability of the stochastic interval delayed Hopfield cellular neural networks. some recent results reported in the literature are generalized. Furthermore, that a Remark and a kind of equivalent description of this stochastic interval delayed Hopfield cellular neural networks are also presented.

Keywords

Hopfield neural nets; Lyapunov methods; cellular neural nets; delays; stability; stochastic systems; Ito formula; Lyapunov function; Razumikhin theorem; norm inequalities; robust stability; stochastic interval delayed Hopfield cellular neural network; time delay; Artificial neural networks; Cellular neural networks; Circuit stability; Robust stability; Stability criteria; Stochastic processes; Itô formula; Lyapunov function; Robust Stability; Stochastic interval delayed Hopfield Cellular Neural Networks; Time-varying delays;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5583221

Filename

5583221